1. Field of the Invention
The present invention relates to workload allocation and power management in a computer system.
2. Description of the Related Art
Large computer systems often include many interconnected servers and other computer hardware consolidated within a central location such as a data center. Computer systems of this size are capable of performing many hundreds or thousands of processing jobs distributed among the many servers. Thus, managing the workload and judiciously allocating the workload among the many servers is an important consideration. Additionally, computer systems consume power commensurate with the amount of workload, and power consumption affects the cost of operating a computer system, as well as the amount of heat and noise generated by the computer system. Therefore, managing power is another important consideration when operating a computer system. Optimizing the efficiency of a computer system helps to minimize expense, heat production, and noise.
Dynamic Voltage Scaling (DVS) or Dynamic Voltage and Frequency Scaling (DVFS) are two types of predictive power management schemes that can be used to manage power in a computer system. Such power management schemes are based on the relationship of power consumption to the core voltage and frequency of processors, which is commonly expressed as P α fV2. These techniques are used to dynamically adjust voltage (DVS) or voltage and frequency (DVFS) on each server based on a prediction of the anticipated performance. The predictive nature of these techniques has an associated level of uncertainty. This uncertainty can lead to excessive energy consumption when the voltage or frequency needed to support a workload is overestimated, and can cause missed demand during periods when the voltage or frequency needed is underestimated.
As the performance and power of computer systems continue to advance, there is an ongoing need for improved workload allocation and power management solutions. In particular, it would be desirable to increase the certainty involved with power and workload management to improve the accuracy and performance of existing predictive power management schemes. Furthermore, it would be desirable to allocate workload evenly across an appropriate number of processors.